This project is to build a ML model to classify the stress level according to different features.
The dataset sourced from Kaggle.
This dataset dives into how working remotely affects stress levels, work-life balance, and mental health conditions across various industries and regions.
With 5,000 records collected from employees worldwide, this dataset provides valuable insights into key areas like work location (remote, hybrid, onsite), stress levels, access to mental health resources, and job satisfaction. It’s designed to help researchers, HR professionals, and businesses assess the growing influence of remote work on productivity and well-being.
Columns:
Employee_ID: Unique identifier for each employee. Age: Age of the employee. Gender: Gender of the employee. Job_Role: Current role of the employee. Industry: Industry they work in. Work_Location: Whether they work remotely, hybrid, or onsite. Stress_Level: Their self-reported level of stress. Mental_Health_Condition: Any mental health condition reported (Anxiety, Depression, etc.). Social_Isolation_Rating: A self-reported rating (1-5) on how isolated they feel. Satisfaction_with_Remote_Work: How satisfied they are with remote work arrangements (Satisfied, Neutral, Unsatisfied).